TY - GEN
T1 - CT and MRI fusion for postimplant prostate brachytherapy evaluation
AU - Dehghan, Ehsan
AU - Le, Yi
AU - Lee, Junghoon
AU - Song, Daniel Y.
AU - Fichtinger, Gabor
AU - Prince, Jerry L.
N1 - Funding Information:
E. Dehghan was with Queen's University and the Johns Hopkins University at the time this work was performed. He was supported by an Ontario Ministry of Research and Innovation Post-Doctoral Fellowship. G. Fichtinger was supported as Cancer Care Ontario Research Chair. This work was also supported by National Institutes of Health/National Cancer Institute (NIH/NCI) under Grants 2R44CA099374 and 1R01CA151395
PY - 2016/6/15
Y1 - 2016/6/15
N2 - Postoperative evaluation of prostate brachytherapy is typically performed using CT, which does not have sufficient soft tissue contrast for accurate anatomy delineation. MR-CT fusion enables more accurate localization of both anatomy and implanted radioactive seeds, and hence, improves the accuracy of postoperative dosimetry. We propose a method for automatic registration of MR and CT images without a need for manual initialization. Our registration method employs a point-to-volume registration scheme during which localized seeds in the CT images, produced by commercial treatment planning systems as part of the standard of care, are rigidly registered to preprocessed MRI images. We tested our algorithm on ten patient data sets and achieved an overall registration error of 1.6 ± 0.8 mm with a running time of less than 20s. With high registration accuracy and computational speed, and no need for manual intervention, our method has the potential to be employed in clinical applications.
AB - Postoperative evaluation of prostate brachytherapy is typically performed using CT, which does not have sufficient soft tissue contrast for accurate anatomy delineation. MR-CT fusion enables more accurate localization of both anatomy and implanted radioactive seeds, and hence, improves the accuracy of postoperative dosimetry. We propose a method for automatic registration of MR and CT images without a need for manual initialization. Our registration method employs a point-to-volume registration scheme during which localized seeds in the CT images, produced by commercial treatment planning systems as part of the standard of care, are rigidly registered to preprocessed MRI images. We tested our algorithm on ten patient data sets and achieved an overall registration error of 1.6 ± 0.8 mm with a running time of less than 20s. With high registration accuracy and computational speed, and no need for manual intervention, our method has the potential to be employed in clinical applications.
KW - CT
KW - MRI
KW - Multi-Modality Registration
KW - Prostate Brachytherapy
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U2 - 10.1109/ISBI.2016.7493345
DO - 10.1109/ISBI.2016.7493345
M3 - Conference contribution
C2 - 28890754
AN - SCOPUS:84978402335
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 625
EP - 628
BT - 2016 IEEE International Symposium on Biomedical Imaging
PB - IEEE Computer Society
T2 - 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
Y2 - 13 April 2016 through 16 April 2016
ER -